Proposed Solution.
In [1]}, we present an unsupervised model and inference method for learning neural MTPP over CTES with missing events. Specifically, we design a coupled-MTPP approach that first models the generative processes of both – observed events and missing events – where the missing events are represented as latent-random variables. Later, we jointly learn the distribution of all events via MTPP using variational inference.
